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Prevalence Visual Search: Optimal Performance and The Description-Experience Gap

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2019, Doctor of Philosophy (PhD), Wright State University, Human Factors and Industrial/Organizational Psychology PhD.
Real-world visual search differs significantly from the laboratory task. One distinct feature is that most targets in real-world visual search are low prevalence. Considering the important practical connections between the laboratory study and applied research, there has been a resurgence in exploring prevalence effects on visual search performance, especially the effect that targets are more likely to be missed when they have low prevalence. Though there is a consensus that target misses are due to a liberal criterion, previous studies failed to consider the potentiality of optimal performance from the perspective of Signal Detection Theory, which also predicts a the liberal criterion shift. Moreover, previous decision making literature has demonstrated that observers subjectively weighted the probability based on the information communications they were given (i. e. the description-experience gap), motivates the current study to explore how target probability communications influence search performance. To explore the hypothesis of optimal performance and the influence of probability communications, the current research assessed observers’ performance from two aspects: behavioral performance and eye movements. The results indicated that with a high penalty on miss errors, observers’ criteria were more liberal toward “target-present” responses. However, the performance was not optimal as expected. The manipulation of information indicated visual search was affected by the way the target prevalence information was given to observers. Specifically, when target prevalence was low, learning prevalence from experience resulted in the belief in more targets and longer search time before quitting compared to the contexts in which observers had been explicitly informed about the target probability. The observed discrepancy narrowed with increased prevalence and reversed when target prevalence was high. There was no clear evidence for the same discrepancy in item fixation time. The observed results were consistent with the previous study that the prevalence effects affected the item fixation time and number of fixated/re-fixated items. However, only information communications interacted with prevalence when accounting for number of re-fixated items as hypothesized. The demonstration that the information communications influence search performance in the current research has implications for the experimental design of future prevalence search studies and can also guide research on prevalence information learning in the future.
Joseph W. Houpt, Ph.D. (Committee Chair)
Valerie Shalin, Ph.D. (Committee Member)
Scott Watamaniuk, Ph.D. (Committee Member)
Christopher Myers, Ph.D. (Committee Member)
92 p.

Recommended Citations

Citations

  • Zhang, H. (2019). Prevalence Visual Search: Optimal Performance and The Description-Experience Gap [Doctoral dissertation, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1559317096524462

    APA Style (7th edition)

  • Zhang, Hanshu. Prevalence Visual Search: Optimal Performance and The Description-Experience Gap. 2019. Wright State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright1559317096524462.

    MLA Style (8th edition)

  • Zhang, Hanshu. "Prevalence Visual Search: Optimal Performance and The Description-Experience Gap." Doctoral dissertation, Wright State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=wright1559317096524462

    Chicago Manual of Style (17th edition)